Detail publikace

Variational Approximation of Long-span Language Models for LVCSR

Originální název

Variational Approximation of Long-span Language Models for LVCSR

Anglický název

Variational Approximation of Long-span Language Models for LVCSR

Jazyk

en

Originální abstrakt

We have presented experimental evidence that (n-gram) variational approximations of long-span LMs yield greater accuracy in LVCSR than standard n-gram models estimated from the same training text.

Anglický abstrakt

We have presented experimental evidence that (n-gram) variational approximations of long-span LMs yield greater accuracy in LVCSR than standard n-gram models estimated from the same training text.

BibTex 


@inproceedings{BUT76377,
  author="Anoop {Deoras} and Tomáš {Mikolov} and Stefan {Kombrink} and Martin {Karafiát} and Sanjeev {Khudanpur}",
  title="Variational Approximation of Long-span Language Models for LVCSR",
  annote="We have presented experimental evidence that (n-gram) variational approximations
of long-span LMs yield greater accuracy in LVCSR than standard n-gram models
estimated from the same training text.",
  address="IEEE Signal Processing Society",
  booktitle="Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011",
  chapter="76377",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Signal Processing Society",
  year="2011",
  month="may",
  pages="5532--5535",
  publisher="IEEE Signal Processing Society",
  type="conference paper"
}